OPERATIONAL SOFTWARE PERFORMABILITY EVALUATION BASED ON MARKOVIAN RELIABILITY GROWTH MODEL WITH SYSTEMABILITY

Abstract

In this paper, we discuss the operational performability evaluation model for the software-based system, introducing the concept of systemability which is defined as the reliability characteristic subject to the uncertainty of the field environment. Assuming that the software system can process the multiple tasks simultaneously and that the arrival process of the tasks follows a nonhomogeneous Poisson process, we analyze the distribution of the number of tasks whose processes can be completed within the processing time limit with the infinite-server queuing theory. Here we take the position that the software reliability characteristic in the testing phase is originally different from that in the operation phase. Then, the software failure-occurrence phenomenon in the operation phase is described with the Markovian software reliability model with systemability, i.e., we consider the randomness of the environmental factor which is introduced to bridge the gap between the software failure-occurrence characteristics during the testing and the operation phases. We derive several software performability measures considering the real-time property; these are given as the functions of time and the number of debugging activities. Finally, we illustrate several numerical examples of the measures to investigate the impact of consideration of systemability on the system performability evaluation.